Project Summary Of the 70,000 new cases of non-Hodgkin?s lymphoma (NHL) diagnosed in 2014, the most common subtype is diffuse large B-cell lymphoma (DLBCL), of these approximately 40% will relapse after standard induction with CHOP-R. Of these patients, the only opportunity for long-term disease control is with CAR T cell therapy, autologous or allogeneic transplant. Many patients are not candidates due to age or co-morbidities, cannot achieve required disease control, or do not have a suitable donor. Additionally, many relapsed indolent and mantle cell lymphoma (MCL) patients eventually exhaust all treatment options are not candidates for aggressive cytotoxic chemotherapy due to co-morbidities or the potential for substantial myelosuppression. Patients with relapsed/refractory (R/R) NHL clearly represent an unmet medical need. Both lenalidomide and blinatumomab have proven, but limited, efficacy in R/R NHL. Lenalidomide has been shown to modulate different components of the immune system by altering cytokine production, regulating T cell co-stimulation and augmenting the NK cell cytotoxicity. Blinatumomab specifically targets the CD19 antigen present on B cells. The inability of blinatumomab to mediate responses or durable responses is likely due to the inability to recruit competent cytotoxic T cells or eventual T cell exhaustion. The current approach will mediate redirection of lenalidomide-mediated, activated, competent, cytotoxic T cells to the malignant CD19+ B cells. UC Davis protocol # PHI-79 (NCI protocol # 9924, Clinicaltrials.gov identifier NCT02568553) examines the relationship between blinatumomab-, or lenalidomide + blinatumomab-mediated T cell activation and response. The phase I portion of the study has been completed and demonstrated the combination was well tolerated with an encouraging ORR of 90% (Poh et al ASH 2019). We are seeking supplemental funds to conduct the ancillary studies associated with this trial, studies which are directly in line with the goals of the City of Hope and UC Davis Comprehensive Cancer Center UM1 grant. Using biospecimens collected from PHI-79, we aim to identify biomarkers for therapeutic response. Our team has extensive experience integrating omic data sets to develop multi-analyte classifiers (biomarkers) for clinical diagnostic tests and have developed computational tools to streamline these efforts. Our specific hypothesis is that composite biomarkers comprised of easily quantifiable immune response elements will be able to predict a patient?s ultimate responsiveness to therapy.